Do you want to publish a course? Click here

Usage of Distinguished Elements to Construct Algorithm to Test Simple Lie Algebras

استخدام العناصر المميزة في إنشاء خوارزمية لاختبار جبور لي البسيط

1058   0   7   0 ( 0 )
 Publication date 2008
  fields Mathematics
and research's language is العربية
 Created by Shamra Editor




Ask ChatGPT about the research

A Lie algebra g over a field F is a vector space together with a bilinear map [ , ] satisfying [x ,x ] = 0 in addition to Jacobi identity . A Lie subalgebra B of a Lie algebra g is said to be a Cartan subalgebra if it is a nilpotent and equals its normalizer, and it is proved that semi simple Lie algebra g decomposes into weight spaces for B. In this scientific paper we present the conception of distinguished element 0 h in finite dimensional semi simple Lie algebra over a field F has characteristic 0 and we will prove that the previous decomposition g into weight spaces for B is the same to decomposition g as a direct sum of h0 ad eigen spaces. This leads us to construct algorithm to test simple Lie algebras. We programmed the previous algorithm to test simple linear Lie algebras over a numeral field by Mathematica 5.0 program where applied this algorithm on semi simple linear Lie algebra SL(3, ) to prove that it is simple.



References used
Carter, R.W. (2005). Lie algebras of finite and affine type, Cambridge university Press , Cambridge . p 36, 46,18,37, 48
Eradman ,K., and Wildon , M.J. (2006). Introduction to Lie algebras, Springer Verlag , London . p 1, 3, 82
Humphreys, J.E. (1972). Introduction to Lie algebras and representation theory, third ed . Springer. p 7,81,82
rate research

Read More

In this scientific paper, we describe an algorithm to test if the weighted Dynkin diagram of type -Cn corresponds to one of the nilpotent orbits of sp2n, then we defined the necessary and sufficient condition on this representative that makes the diagram even. We applied this algorithm on one of the weighted Dynkin diagrams of type –C3 to prove that it is true
Our aim of this paper is to study some properties of Lie groups and fuzzy Lie groups in many statements. So we can determine some properties of Lie groups and we prove on its by the Topological spaces constructing on the Lie groups as the Zero- di mensional space and connected space. In fuzzy Lie groups, we can also get some results and we prove on its in this paper.
We propose a rolling version of the Latent Dirichlet Allocation, called RollingLDA. By a sequential approach, it enables the construction of LDA-based time series of topics that are consistent with previous states of LDA models. After an initial mode ling, updates can be computed efficiently, allowing for real-time monitoring and detection of events or structural breaks. For this purpose, we propose suitable similarity measures for topics and provide simulation evidence of superiority over other commonly used approaches. The adequacy of the resulting method is illustrated by an application to an example corpus. In particular, we compute the similarity of sequentially obtained topic and word distributions over consecutive time periods. For a representative example corpus consisting of The New York Times articles from 1980 to 2020, we analyze the effect of several tuning parameter choices and we run the RollingLDA method on the full dataset of approximately 4 million articles to demonstrate its feasibility.
The aim of this paper is to use some properties of Lie groups and fuzzy Lie groups in many statements to prove on some open problems, so we can prove on the lemma(1) and (2).
Much of recent progress in NLU was shown to be due to models' learning dataset-specific heuristics. We conduct a case study of generalization in NLI (from MNLI to the adversarially constructed HANS dataset) in a range of BERT-based architectures (ada pters, Siamese Transformers, HEX debiasing), as well as with subsampling the data and increasing the model size. We report 2 successful and 3 unsuccessful strategies, all providing insights into how Transformer-based models learn to generalize.

suggested questions

comments
Fetching comments Fetching comments
Sign in to be able to follow your search criteria
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا